Environmental Science & Techonology: Data Analytics Determines Co-occurrence of Odorants in Raw Water and Evaluates Drinking Water Treatment Removal Strategies


A complex dataset with 140 sampling events was generated using triple quadrupole gas chromatography-mass spectrometer to track the occurrence of 95 odorants in raw and finished water from 98 drinking water treatment plants in 31 cities across China. Data analysis identified more than 70 odorants with concentrations ranging from not detected to thousands of ng/L. In raw water, Pearson correlation analysis determined that thioethers, non-oxygen benzene-containing compounds, and pyrazines were classes of chemicals that co-occurred, and geosmin and p(m)-cresol, as well as cyclohexanone and benzaldehyde, also co-occurred, indicating similar natural or industrial sources. Based on classification and regression tree analysis, total dissolved organic carbon and geographical location were identified as major factors affecting the occurrence of thioethers. Indoles, phenols, and thioethers were well-removed through conventional and advanced treatment processes, while some aldehydes could be generated. For other odorants, higher removal was achieved by ozonation-biological activated carbon (39.3%) compared to the conventional treatment process (14.5%). To our knowledge, this is the first study to systematically identify the major odorants in raw water and determine suitable treatment strategies to control their occurrence by applying data analytics and statistical methods to the complex dataset. These provide informative reference for odor control and water quality management in drinking water industry.

In Environmental Science & Technology
Ming Su
Ming Su
Associate Professor of Environmental Engneering

My research interest is water quality problems in drinking water bodies, with a focus on harmful algal blooms and associated taste & odor problems.

Jianwei Yu
Associate Professor of Environmental Engineering
Min Yang
Min Yang
Professor of Environmental Engneering